This work proposes a spherical-orthogonal-symmetric Haar wavelet to decompose and reconstruct spherical iris signals to obtain stronger geometric features of iris surface. It compares its feature extraction abilities of spherical harmonics, semi-orthogonal and nearly orthogonal spherical Haar wavelet. The developed spherical-orthogonal-symmetric Haar wavelet with a convolutional neural network is also proposed for drivers’ iris recognition. It can effectively capture the local fine features of iris spherical surface, and has stronger ability of iris recognition than semi-orthogonal or nearly orthogonal spherical Haar wavelet bases.


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    Title :

    Spherical-Orthogonal-Symmetric Haar Wavelet for Driver's Visual Detection


    Contributors:
    Hou, Yuhong (author) / Wu, Edmond Q. (author) / Cao, Zhengtao (author) / Xu, Xin (author) / Zhu, Li-Min (author) / Yu, Mengsun (author)

    Published in:

    Publication date :

    2023-03-01


    Size :

    2655264 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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